Harvard Business Review
by Preethika Sainam, Seigyoung Auh, Richard Ettenson, Yeon Sung Jung
July 27, 2022
Executive Summary by:
Joaquim Cardoso MSc.
health revolution . institute
analytics informed health care unit
July 28, 2022
Every company is trying to capitalize on the promise of data and analytics.
While a few leading firms like Amazon and Alibaba seem to have cracked the code, most are still finding their way and many remain unsure even where to start. A large majority of senior leaders are not satisfied with the outcomes delivered through analytics.
To find out, the authors surveyed more than 300 senior executives across B2B industries about data-driven decision-making in their organizations and their performance on seven dimensions of analytics capability:
- Culture: The degree of consensus on the value of data and analytics as a strategic asset
- Leadership commitment: The extent to which senior leaders “walk the talk” when it comes to data and analytics
- Operations and structure: The level of development of structures and policies that support access to data for those who need it
- Skills and competencies: The ability to hire the right people and provide adequate training and support for them
- Analytics-strategy alignment: How effectively analytics complements both short- and long-term strategy
- Proactive market orientation: The degree to which data and analytics allow the organization to keep pace with and anticipate evolving customer needs
- Employee empowerment: The extent to which people throughout the organization are encouraged to pursue creative data capture and analytical methodologies
On these findings, we identified three tiers of companies: data and analytics laggards, strivers, and leaders.
The authors created a tool — available below — that helps leaders identify where their firm falls on this spectrum and the organizational characteristics and capabilities they may need to develop to further advance on their analytics journey.
The results can reveal a company’s analytics strengths or weaknesses, help it prioritize investments and allocate resources, provide benchmarks for gauging progress, and ultimately help it become more data driven and competitive.
By using the diagnostic tool, companies can create a unique profile of their data and analytics capabilities; and, …
with the playbook, they can then address areas of weaknesses and enhance their strengths, driving an ongoing data and analytics transformation that can deliver real sustained competitive advantage.
ORIGINAL PUBLICATION (excerpt of the long version)
How Well Does Your Company Use Analytics?
Harvard Business Review
by Preethika Sainam, Seigyoung Auh, Richard Ettenson, Yeon Sung Jung
July 27, 2022
Every company is trying to capitalize on the promise of data and analytics.
While a few leading firms like Amazon and Alibaba seem to have cracked the code, most are still finding their way and many remain unsure even where to start.
A 2021 study by NewVantage found only 39% of executives believe their organizations manage data as an asset, and even fewer (24%) view their companies as being data-driven.
Likewise VentureBeat found, in their 2021 survey, that just 13% of executives believe their organizations are delivering on their data strategy.
These underwhelming findings are consistent with earlier studies by McKinsey, Deloitte, and BCG that revealed a large majority of senior leaders are not satisfied with the outcomes delivered through analytics.
What separates leaders from these lagging companies, and how can firms struggling with the analytics mandate catch up with — and even surpass — their competitors?
To find out, we surveyed more than 300 senior executives across B2B industries about data-driven decision-making in their organizations and their performance on seven dimensions of analytics capability:
- Culture: The degree of consensus on the value of data and analytics as a strategic asset
- Leadership commitment: The extent to which senior leaders “walk the talk” when it comes to data and analytics
- Operations and structure: The level of development of structures and policies that support access to data for those who need it
- Skills and competencies: The ability to hire the right people and provide adequate training and support for them
- Analytics-strategy alignment: How effectively analytics complements both short- and long-term strategy
- Proactive market orientation: The degree to which data and analytics allow the organization to keep pace with and anticipate evolving customer needs
- Employee empowerment: The extent to which people throughout the organization are encouraged to pursue creative data capture and analytical methodologies
On these findings, we identified three tiers of companies: data and analytics laggards, strivers, and leaders.
We then created a tool — available below — that helps leaders identify where their firm falls on this spectrum and the organizational characteristics and capabilities they may need to develop to further advance on their analytics journey.
The results can reveal a company’s analytics strengths or weaknesses, help it prioritize investments and allocate resources, provide benchmarks for gauging progress, and ultimately help it become more data driven and competitive.
It can also help create a common language and mindset across the organization which will help create alignment and traction across the organization — and reveal differing perceptions of the firm’s capabilities.
Further, it can help illuminate the views of those on the front lines or otherwise outside of the leadership circle whose customer-facing responsibilities will play a vital role in the transformation effort’s progress and success.
The results can reveal a company’s analytics strengths or weaknesses, help it prioritize investments and allocate resources, provide benchmarks for gauging progress, and ultimately help it become more data driven and competitive.
Assess your capabilities
Not every organization begins its journey from the same place.
Some companies’ capabilities are well developed while others are rudimentary. Regardless, each company needs to answer three questions as it works to enhance its capabilities: What is our current level of proficiency? In what areas do we need to improve? And what do we need to do to optimize our data and analytics performance?
To assess your company’s data and analytics proficiency, assemble a set of core employees and other internal stakeholders representing a range of management levels and business functions.
Be sure to engage a diverse sample of staff who will lead and manage teams in the transformation effort (e.g., executives in IT, marketing, and even HR), as well as front-line employees who will be affected by its implementation, such as those in sales, marketing, and customer service.
Think of this exercise as a small group workshop with representation that will provide leadership with insights from informed discussion among participants leading to an “enterprise-wide reality check” of the company’s current capabilities.
Have each workshop participant individually answer the diagnostic-tool questions below using the one (strongly disagree) to five (strongly agree) scale for each item.
Next, aggregate and average respondents’ scores on each of the seven analytics capabilities dimensions (culture, leadership commitment, and so on).
This will provide a single, overall score on each dimension, revealing broad areas where the company may be performing well, or not.
If the findings reveal areas of notable weakness, leaders may want to focus first on these to create a stable analytics foundation.
In other cases, the priority may be to continue building and enhance areas where the tool reveals moderate levels of performance.
Conversely, high scores can reveal areas where continued (even modest) investments can help ensure no decline in performance in those areas essential to maintain business success.
Top performing companies also can double down on strengths that already confer competitive advantage to put them even further ahead of the analytics strivers and laggards.
While looking at the scores for individual questions can help leaders know where to focus, it can also be valuable to periodically calculate a single, broader company metric by averaging all scores on the seven analytics dimensions.
This aggregate measure can allow leadership to track the company’s overall progress over time or compare progress across subsidiaries.
Gauge employees’ consensus
If a company is to move ahead on its analytics journey it must also strive to build consensus among key players and work out where differences in perceptions of capabilities may exist.
As the workshop participants represent different functions, levels of management, and lines of business, their individual scores can expose hidden areas of disagreement.
If representatives from, say, IT and marketing, or the C-suite and HR) have dramatically different perspectives on the firm’s data and analytics capabilities, it’s worth investigating and addressing it.
This can be done with further informal workshop discussions that focus specifically on areas of disagreement to surface a more accurate picture and strategies for shoring up any revealed weakness.
Such revealed differences may potentially signal a red flag on firm performance such as sales or profit.
Gaining consensus among employees also enables an additional benefit — an aligned mindset and use of common language among workshop participants.
Ultimately, this shared perspective will be socialized across the organization as insights and action steps from the workshop are disseminated through the ranks.
For example, when diverging perspectives emerge in the workshops, understanding why there is disagreement — for instance, one function is aware of capabilities or initiatives that another isn’t — can help leadership design targeted communications that inform and align employee perceptions organization-wide.
In other cases, gaps in perceptions among workshop members may accurately reveal fundamental shortcomings in analytics capabilities that require long-term cultural interventions or the need to immediately hire for critical skills that are lacking.
Fix weaknesses and enhance strengths
Firms that complete our diagnostic typically find that they have a mix of strengths and weaknesses.
Depending on their industry sector and competitive content, company leaders should focus their attention on those dimensions that are essential to providing superior and sustainable business performance and address key areas where they are performing least well.
For lagging companies, this will mean fixing fundamental areas of weakness; for leading companies it will mean optimizing performance on dimensions where they still have room to grow.
Drawing on our analysis of leading companies, we created the playbook below that leadership can use to improve the company’s performance on each dimension.
Every company is somewhere along an open-ended journey to achieve data and analytics superiority.
While there is no final destination — there will always be more to do — there is a roadmap for efficiently and strategically progressing on the journey.
By using our diagnostic tool, companies can create a unique profile of their data and analytics capabilities; and, with our playbook, they can then address areas of weaknesses and enhance their strengths, driving an ongoing data and analytics transformation that can deliver real sustained competitive advantage.
By using our diagnostic tool, companies can create a unique profile of their data and analytics capabilities; …
… and, with our playbook, they can then address areas of weaknesses and enhance their strengths, driving an ongoing data and analytics transformation that can deliver real sustained competitive advantage.
Originally published at https://hbr.org on July 27, 2022.
